Signal Correction Research Articles

Comparison of Reflectance and Interactance Modes of Visible and Near-Infrared Spectroscopy for Predicting Persimmon Fruit Quality

The principal aim of this work was to compare the ability of measurement technique among interactance and reflectance in predicting soluble solids content (SSC), ascorbic acid (ASC) and firmness of intact persimmon fruit by using visible/short-wave near-infrared (Vis/SWNIR) spectroscopy. Calibration models were developed by partial least square (PLS) regression that related near-infrared (NIR) spectra to reference values. The root mean square errors of calibration (RMSEC), the root mean square errors of prediction (RMSEP), the correlation coefficients of calibration (Rcal) and prediction (Rval) and the ratio of performance to deviation (RPD) were used to consider the model accuracy. The PLS models from interactance showed satisfactory performance, providing better prediction results than reflectance technique in all parameters. ASC and firmness presented the best calibration models. ASC, Rval = 0.92, RMSEP = 5.56 (mg kg-1 FW) and RPD = 2.54 were attained when using orthogonal signal correction (OSC) pretreatment. Firmness, Rval = 0.89, RMSEP = 4.21 N and RPD = 2.14 were also achieved using OSC pretreatment. These findings highlighted the potential of Vis/SWNIR spectroscopy with the multivariate calibration technique to be applied for evaluating ASC and firmness of fresh persimmon fruit.

Large-Scale Boron-Lined Neutron Detection Systems as a 3He Alternative for Cosmic Ray Neutron Sensing

Cosmic-Ray neutron sensors are widely used to determine soil moisture on the hectare scale. Precise measurements, especially in the case of mobile application, demand for neutron detectors with high counting rates and high signal-to-noise ratios. For a long time Cosmic Ray Neutron Sensing (CRNS) instruments have relied on $^3$He as an efficient neutron converter. Its ongoing scarcity demands for technological solutions using alternative converters, which are $^6$Li and $^{10}$B. Recent developments lead to a modular neutron detector consisting of several $^{10}$B-lined proportional counter tubes, which feature high counting rates via its large surface area. The modularity allows for individual shieldings of different segments within the detector featuring the capability of gaining spectral information about the detected neutrons. This opens the possibility for active signal correction, especially useful when applied to mobile measurements, where the influence of constantly changing near-field to the overall signal should be corrected. Furthermore, the signal-to-noise ratio could be increased by combining pulse height and pulse length spectra to discriminate between neutrons and other environmental radiation. This novel detector therefore combines high-selective counting electronics with large-scale instrumentation technology.

Design and development of material behavior of line follower automated vehicle

The model having two types of I.R LED (emitter), photoelectric sensor which provide the signal to motor via the transistor. The LED which emit the light it is wrapped up by sensors in the white surface. The Line follower robot is model which can identify and track the line drawn on the floor. Hence this model must be in sense the line with IR sensors. The processor is used to make a decision the correct signals. In this study, discuss the process design, development of material behavior, applications etc. The Line follower robot is a mobile based machine that can detect and follow the line drawn on the floor. This kind of model should sense the Infrared Ray sensor that fitted in the system.

The role of short‐term contracts and subsidies in licensing

An innovator without production facilities owns a patented invention that lasts two periods, and looks for the best licensing arrangement with a producer that has private information about the market value of the invention. The license is either a single long‐term contract in force over both periods or a series of short‐term contracts, one per period. Under short‐term contracts, the licensee can strategically signal the value of the invention with its level of production in the first period and thus influence the terms of the contract in the second period. We show that the licensor prefers successive short‐term contracts rather than a single long‐term contract for intermediate‐level probabilities of dealing with an efficient licensee, while the first‐period contract may optimally include a per‐unit subsidy (a negative royalty rate) in order to correct signaling distortions in the licensee’s production for this period. We also show that prohibiting such subsidies can lead to welfare losses.

Exploring a public database to evaluate consumer preference and aroma profile of lager beers by comprehensive two-dimensional gas chromatography and partial least squares regression discriminant analysis

In this paper is reported a proof of concept study to evaluate the usage of a public metadata base about beers to guide chemical interpretation of volatile organic compounds (VOC) profiling. 1,569,641 consumers’ evaluations were collected from Untappd® platform and used to define a property of interest according to beer preference. 14 brands of beers from lager family were divided in two groups, first one containing samples with low consumers’ ratings and the second with brands that exhibited high evaluations. VOC profiles were extracted by headspace solid phase microextraction (HS-SPME) and analyzed using comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC × GC-MS). To correlate the VOC profile and consumers’ preference, unfolded-partial least squares discriminant analysis (U-PLS-DA) with orthogonal signal correction (OSC) were employed. The mathematical model successfully classified all the beer samples. Furthermore, a template match protocol identified 31 compounds related to consumers’ preference. This proof of concept paper revealed the potential usage of public metadata bases for comprehensive chemical interpretation of VOC profiling in foodomics.

Structures of signal correction circuits based on double modular redundancy with computation control

Structures of signal correction circuits based on double modular redundancy with computation control

Attenuated Total Reflection Fourier Transform Infrared Spectroscopy combined with chemometric modelling for the classification of clinically relevant Enterococci.

Attenuated Total Reflection Fourier Transform Infrared (ATR-FT-IR) Spectroscopy and chemometric modelling, including soft independent modelling by class analogy (SIMCA), partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM), were applied to attempt to discriminate 60 clinical isolates of Enterococcus faecium and Enterococcus faecalis and hence evaluate the performance of the spectroscopic approach in identifying enterococci infections. The bacterial samples were identified by polymerize chain reaction (PCR) amplification and their ATR-FT-IR spectra acquired. Spectra were processed to the second derivative using the Savitzky-Golay algorithm and normalized using extended multiplicative signal correction employing the UnscramblerX (CAMO, Norway) software package. Multivariate classification models and their performance were evaluated using Cohen's Kappa coefficient. Principal component analysis (PCA) score plots showed separate clusters of spectra related to membership to E. faecium and E. faecalis, with this explained by bands assigned to PO2 (1230cm-1 ), P-O-C (1114cm-1 ), monosubstituted alkene (997, 987cm-1 ) and C-O (1070, 1055, 1036cm-1 ) corresponding to teichoic acids, polysaccharides and peptidoglycan from the cell wall in PCA and PLS-DA loading plots. The best classification model for E. faecium and E. faecalis is SVM, indicating via highest Kappa score. The classification coefficient between SIMCA, PLS-DA, SVM and PCR as reference method were 0·59, 0·9 and 1, respectively, shown as the Kappa scores. The main spectral differences observed between the two clinically relevant enterococci species were associated with changes in the teichoic acid content of cell walls. With regard to the binary classification method, SVM was found to be the best performing classification model, providing the highest correlation with the PCR results. The study shows that ATR-FT-IR spectroscopy in combination with chemometric modelling can be applied for the phenotypic identification and discrimination of clinically relevant and similar enterococcal species.

A retrospective physiological noise correction method for oscillating steady-state imaging.

Oscillating steady-state imaging (OSSI) is an SNR-efficient steady-state sequence with sensitivity suitable for FMRI. Due to the frequency sensitivity of the signal, respiration- and drift-induced field changes can create unwanted signal fluctuations. This study aims to address this issue by developing retrospective signal correction methods that utilize OSSI signal properties to denoise task-based OSSI FMRI experiments. A retrospective denoising approach was developed that leverages the unique signal properties of OSSI to perform denoising without a manually specified noise region of interest and works with both voxel timecourses (oscillating steady-state correction [OSSCOR]) or FID timecourses (F-OSSCOR). Simulations were performed to estimate the number of principal components optimal for denoising. In vivo experiments at 3 T field strength were conducted to compare the performance of proposed methods against a standard principal component analysis-based method, measured using mean t score within an region of interest, number of activations, and mean temporal SNR. Correction using OSSCOR was significantly better than the standard method in all metrics. Correction using F-OSSCOR was not significantly different from the standard method using an equal number of principal components. Increasing the number of OSSCOR principal components decreased activation strength and increased the number of suspected false positives. However, increasing the number of principal components in F-OSSCOR increased activation strength with little to no increase in false activation. Both OSSCOR and F-OSSCOR substantially reduce physiological noise components and increase temporal SNR, improving the functional results of task-based OSSI functional experiments. F-OSSCOR demonstrates a proof of concept utilization of coil-localized FID signal information for physiological noise correction.

GLOBAL NAVIGATION SATELLITE SYSTEMS AND THEIR ROLE IN PRECISION AGRICULTURE TECHNOLOGIES

Today, global navigation satellite systems are being implemented in many structural units of the Ukrainian economic complex, many spheres of human activity, and every year they continue to develop. One of the main feature of these satellite systems is the requirements for high accuracy and speed of received data. They provide the opportunity to reduce operating costs and increase the efficiency of use of equipment and other resources. Therefore, the use of navigation satellite systems for controlling machine units, establishing their location, monitoring soil condition and yield mapping is becoming increasingly relevant today. The subject of study in this article were global navigation satellite systems NAVSTARGPS (USA), GLONASS (RF), GALILEO (EU), BEIDOU (China) and regional navigation systems NavIC (India) and QUASI-ZENITH (Japan). The purpose of the work was to clarify and establish the main characteristics of global navigation satellite systems and their role in the implementation of precision agriculture technologies. The task of the work was: to analyze the functional characteristics of global positioning satellite systems and their main elements; to find out principles of operation of systems: navigation, coordinates, time; to establish the accuracy of navigation systems; to substantiate the role of global positioning satellite systems in the effective implementation of precision agriculture technologies in agriculture. The research methodology was based on the method of materialistic dialectics, methods of analysis and synthesis of both information from official sources and information from the works of other researchers. Two major operators of satellite navigation systems the NAVSTAR GPS and GLONASS, which are similar in many respects, have been identified in the scientific work. Among the distinctive features there are the nature of the location, the motion of satellites in orbits and their total number, methods of encoding the CDMA and FDMA signals, the use of different coordinate systems WGS-84 and PZ90.11. As for the other two satellite navigation systems GALILEO and BEIDOU, they are developing rapidly with great ambition and potential. It is established that at the present time the accuracy of determining the coordinates of the GLONASS system is inferior to the performance of the American satellite navigation system GPS. GLONASS provides more accurate positioning in the northern latitudes and GPS in the middle. It is noted that the positioning accuracy of machine units for the implementation of precision farming technologies can be improved (from 2 to 20 cm) due to differential signal correction with the help of free and commercial wideband satellite navigation subsystems. These services will allow to implement the tasks of precision driving, and therefore, to ensure the accurate implementation of sowing material, fertilizers and herbicides to spare them, accurate inter-row cultivation of industrial crops, accurate harvesting, etc., when performing agro-technological operations using ground vehicles and landless vehicles.

Extended multiplicative signal correction to improve prediction accuracy of protein content in weathered sorghum grain samples

AbstractBackground and objectivesSorghum grains may be subjected to weathering damage in the field as naked grains on the panicle are exposed to adverse environmental conditions during grain development or dry down before harvest. A near infrared (NIR) protein calibration model did not work as expected for weathered grains. Extended multiplicative signal correction was tested as a preprocessing method for spectra to improve the prediction accuracy of the model when weathered grain samples are evaluated.FindingsNIR spectra of weathered sorghum grain samples showed marked distortions with a higher apparent absorbance at lower wavelengths in the 950–1650 nm spectral range. A partial least squares calibration developed with sound grain samples using spectra preprocessed with multiplicative signal correction (MSC) predicted protein content of validation sample set of sound grains with a root mean square error of prediction (RMSEP) = 0.67% and coefficient of determination (r2) = 0.83. However, performance of this calibration model dropped with RMSEP = 13.14% and r2 = 0.04 when used to predict proteins in weathered grain samples. Introduction of weathered grain spectra to the calibration improved predictive performance with RMSEP = 0.92% and r2 = 0.69. Application of extended multiplicative scatter correction (EMSC) to preprocess the spectra of the calibration with weathered grain samples enhanced the prediction performance with RMSEP = 0.61% and r2 = 0.85.ConclusionsInclusion of weathered grain spectra in the calibration and preprocessing spectra with EMSC markedly improved the robustness of the sorghum protein calibration.Significance and noveltySorghum breeders using NIR spectroscopy for evaluation of protein levels in sorghum breeding lines can get the weathered grain samples also analyzed for protein levels by using this method.

Complex confounder-corrected R2* mapping for liver iron quantification with MRI.

MRI-based R2* mapping may enable reliable and rapid quantification of liver iron concentration (LIC). However, the performance and reproducibility of R2* across acquisition protocols remain unknown. Therefore, the objective of this work was to evaluate the performance and reproducibility of complex confounder-corrected R2* across acquisition protocols, at both 1.5T and 3.0T. In this prospective study, 40 patients with suspected iron overload and 10 healthy controls were recruited with IRB approval and informed written consent and imaged at both 1.5T and 3.0T. For each subject, acquisitions included four different R2* mapping protocols at each field strength, and an FDA-approved R2-based method performed at 1.5T as a reference for LIC. R2* maps were reconstructed from the complex data acquisitions including correction for noise effects and fat signal. For each subject, field strength, andR2* acquisition, R2* measurements were performed in each of the nine liver Couinaud segments and the spleen. R2* measurements were compared across protocols and field strength (1.5T and 3.0T), and R2* was calibrated to LIC for each acquisition and field strength. R2* demonstrated high reproducibility across acquisition protocols (p > 0.05 for 96/108 pairwise comparisons across 2 field strengths and 9 liver segments, ICC > 0.91 for each field strength/segment combination) and high predictive ability (AUC > 0.95 for four clinically relevant LIC thresholds). Calibration of R2* to LIC was LIC = - 0.04 + 2.62 × 10-2 R2* at 1.5T and LIC = 0.00 + 1.41 × 10-2 R2* at 3.0T. Complex confounder-corrected R2* mapping enables LIC quantification with high reproducibility across acquisition protocols, at both 1.5T and 3.0T. • Confounder-corrected R2* of the liver provides reproducible R2* across acquisition protocols, including different spatial resolutions, echo times, and slice orientations, at both 1.5T and 3.0T. • For all acquisition protocols, high correlation with R2-based liver iron concentration (LIC) quantification was observed. • The calibration between confounder-corrected R2* and LIC, at both 1.5T and 3.0T, is determined in this study.

A Hierarchical Hand Gesture Recognition Framework for Sports Referee Training-Based EMG and Accelerometer Sensors.

To cultivate professional sports referees, we develop a sports referee training system, which can recognize whether a trainee wearing the Myo armband makes correct judging signals while watching a prerecorded professional game. The system has to correctly recognize a set of gestures related to official referee's signals (ORSs) and another set of gestures used to intuitively interact with the system. These two gesture sets involve both large motion and subtle motion gestures, and the existing sensor-based methods using handcrafted features do not work well on recognizing all kinds of these gestures. In this work, deep belief networks (DBNs) are utilized to learn more representative features for hand gesture recognition, and selective handcrafted features are combined with the DBN features to achieve more robust recognition results. Moreover, a hierarchical recognition scheme is designed to first recognize the input gesture as a large or subtle motion gesture, and the corresponding classifiers for large motion gestures and subtle motion gestures are further used to obtain the final recognition result. Moreover, the Myo armband consists of eight-channel surface electromyography (sEMG) sensors and an inertial measurement unit (IMU), and these heterogeneous signals can be fused to achieve better recognition accuracy. We take basketball as an example to validate the proposed training system, and the experimental results show that the proposed hierarchical scheme considering DBN features of multimodality data outperforms other methods.

Preliminary analysis of central paroxysmal positional vertigo

Objective: To explore the possible pathogenesis of central paroxysmal positional vertigo (CPPV) by analyzing its clinical manifestations and characteristics. Methods: The clinical data of 3 patients with CPPV, including 1 male and 2 females, aged 36, 14 and 70 years old respectively, were collected from the Department of Otorhinolaryngology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences from June 2014 to June 2018. The clinical symptoms, nystagmus, other central ocular motor abnormalities, MRI, PET-CT, and laboratory findings were analyzed retrospectively. Results: All patients showed transient vertigo and nystagmus induced by head changes relative to gravity, but the characteristics of nystagmus did not conform to the typical characteristics of nystagmus in benign paroxysmal positional vertigo. None of patients response to repositioning maneuvers, and all patients presented with the signs of abnormal visual oculomotor system or other symptoms of central system. MRI, PET-CT and blood biochemical tests confirmed that the causes of CPPV in the patients were chronic hemorrhage, inflammation and paraneoplastic cerebellar degeneration. Although the etiology of the three cases is different, the lesion site is involved in the central velocity storage mechanism. Conclusion: The damage of central velocity storage mechanism may lead to the damage of feedback rotation signal correction pathway, and CPPV appears when the head position changes relative to gravity.

Algorithmic Correction of Magnetometer Device Errors

The problems of using gradient measurements in magnetic exploration are considered. In many cases, to solve various geological problems, information on the intensity of the geomagnetic field and its gradients, as measured by special equipment, is important. The results of the development and construction of a three-component fluxgate magnetometer-gradiometer intended for measuring on the earth’s surface the absolute values of the three components of the geomagnetic field strength vector and the corresponding three components of the gradient are presented. Installation in the device of additional measuring sensors – accelerometers, enables one to calculate the orientation of these vectors in space. The device of the magnetometer-gradiometer is described, its functional diagram and the principle of operation are presented. The set of instrumental errors arising in the manufacture of three-axis systems of fluxgates and accelerometers designed for measuring the components of the geomagnetic field strength and determining the orientation of the device is considered. A method of finding instrument errors and algorithmic correction of information signals that come from measuring sensors is presented. It is shown that this method provides a significant increase in measurement accuracy. Examples of field testing of the device are given. The presented magnetometer-gradiometer can be used to accurately localize tectonic disturbances, low-power zones of magnetic mineralization, previously identified ore bodies and determine the details of their structure.

Energy resolution and linearity of XENON1T in the MeV energy range

Xenon dual-phase time projection chambers designed to search for weakly interacting massive particles have so far shown a relative energy resolution which degrades with energy above sim 200 keV due to the saturation effects. This has limited their sensitivity in the search for rare events like the neutrinoless double-beta decay of ^{136} hbox {Xe} at its Q value, Q_{beta beta }simeq 2.46,hbox {MeV}. For the XENON1T dual-phase time projection chamber, we demonstrate that the relative energy resolution at 1,sigma /mu is as low as (0.80 pm 0.02) % in its one-ton fiducial mass, and for single-site interactions at Q_{beta beta }. We also present a new signal correction method to rectify the saturation effects of the signal readout system, resulting in more accurate position reconstruction and indirectly improving the energy resolution. The very good result achieved in XENON1T opens up new windows for the xenon dual-phase dark matter detectors to simultaneously search for other rare events.

A New Approach of Position Sensorless Control for Brushless DC Motor

Background: Position sensorless control technique for Permanent Magnets-Brush Less Direct Current (PM-BLDC) motor drive is considered in this paper. Materials and Methods: A new estimation based on sensorless technique is proposed for PMBLDC motor. Artificial Neural Network (ANN) is aided for the purpose. Results: The inputs to the ANN are the voltages of PM-BLDC motor and it estimates the sample signals to feed Zero Crossing Point (ZCP) detection circuit. The ZCP detection circuit provides ZCP signals for commutation logic which gives the commutation sequence to power switches. In order to provide the correct sample signal to ZCP detection circuit, the ANN is well trained by Genetic Algorithm (GA). The proposed sensor less control model is implemented in MATLAB/SIMULINK working platform. Conclusion: Field Programmable Gate Array (FPGA) is used to implement the proposed method. Experimental results verify the analysis and demonstrate the advantages of the proposed method.

Improving forest burn severity estimations with partial least squares regression and orthogonal signal correction methods in Daxing’an Mountains, China

Several indices and simple empirical models and ratios of single band from pre- and post-fire Landsat images have been developed to estimate and/or map burn severity. However, these models and indices are usually site-, time- and vegetation-dependent and their applications are limited. The Daxing’an Mountains range has the largest forested area in China and is prone to wildfires. Whether or not the existing models can effectively characterize the burn severity over a large region is unclear. In this study, we used the orthogonal signal correction method based on partial least squares regression (PLSR) to select those variables that better interpret the variance of burn severity. A new index and other commonly used indices were used to construct a new, multivariate PLSR model which was compared with the popular single variable models, according to three assessment indices: relative root mean square error (RMSE%), relative bias (RE%) and Nash–Sutcliffe efficiency (NSE%). The results indicate that the multivariate PLSR model performed better than the other single variable models with higher NSE% (68.2% vs. 67.8%) and less RE% (3.7% vs. − 8.7%), while achieving almost the same RMSE%. We also discuss the spectral characteristics of the four selected variables for constructing the multivariate PLSR model and their correlation with the field burn severity data. The new model developed from this study should help to better understand the patterns of forest burn severity and assist in vegetation restoration efforts in the region.

Cell Competition, the Kinetics of Thymopoiesis, and Thymus Cellularity Are Regulated by Double-Negative 2 to 3 Early Thymocytes

Cell competition in the thymus is a homeostatic process that drives turnover. If the process is impaired, thymopoiesis can be autonomously maintained for several weeks, but this causes leukemia. We aimed to understand the effect of cell competition on thymopoiesis, identify the cells involved, and determine how the process is regulated. Using thymus transplantation experiments, we found that cell competition occurs within the double-negative 2 (DN2) and 3 early (DN3e) thymocytes and inhibits thymus autonomy. Furthermore, the expansion of DN2b is regulated by a negative feedback loop that is imposed by double-positive thymocytes and determines the kinetics of thymopoiesis. This feedback loop affects the cell cycle duration of DN2b, in a response controlled by interleukin 7 availability. Altogether, we show that thymocytes do not merely follow a pre-determined path if provided with the correct signals. Instead, thymopoiesis dynamically integrates cell-autonomous and non-cell-autonomous aspects that fine-tune normal thymus function.

Temperature, turbidity, and the inner filter effect correction methodology for analyzing fluorescent dissolved organic matter in urban sewage.

Dissolved organic matter (DOM) will be increasingly monitored by means of in situ fluorescence spectroscopy devices in order to supervise wastewater treatment plant efficiency, due to their ease of implementation and high-frequency measurement capacity. However, fluorescence spectroscopy measurements are reported to be sensitive to the sample matrix effects of temperature, the inner filter effect (IFE), and turbidity. Matrix effect estimation tests and signal correction have been developed for DOM (tyrosine-like, tryptophan-like, and humic substances-like fluorescent compounds) fluorescence measurements in unfiltered urban sewage samples. All such tests are conducted in temperature, absorbance, and turbidity ranges representative of urban sewage. For all fluorophores studied, an average of 1% fluorescence intensity decrease per degree (°C) of temperature increase could be observed. Protein-like fluorescent compound signals were found to be significantly affected by turbidity (0 to 210 NTU) and IFE (absorbance 254nm > 0.200). Only temperature needs to be corrected for humic substances-like fluorescent compounds since other effects were not observed over the studied ranges of absorbance and turbidity. The fluorescence intensity correction method was applied first to each matrix effect separately and then combined by using a sequential mathematical correction methodology. An efficient methodology for determining the matrix effect correction equations for DOM fluorescence analysis into unfiltered urban sewage samples has been highlighted and could be used for in situ fluorescence measurement devices.

Signal correction for combinational automation devices on the basis of Boolean complement with control of calculations by parity

Simpler than known structure of the system with error correction in calculations is proposed based on duplication and triplication of blocks with majority principle of choosing the values of signals. It is advisable to use the new fault-tolerant structure for automation devices with combinational logic. In fault-tolerant structure synthesis, the parity method is used to establish the fact of a fault in the main logic unit and the logical complement method is used determine incorrectly calculated output functions and to generate signals for their correction. The method also allows to adjust the values of incorrectly calculated functions. Structural diagram and description of error correction system are given. The synthesis algorithm of control equipment is described with minimization of the technical implementation complexity. The experiment results with control combinational circuits are given, confirming the high efficiency of proposed system structure with error correction.